Decision Tree Algorithm Application for Diagnosis of Mental Disorders Symptoms

Nowadays, the incidence of mental illness in the world population has been growing, so it is necessary to improve how the diagnosis is made. Diagnostic methods structured in an interview format are considered the best for collecting and analyzing symptoms. However, most health professionals reveal that they do not use such methods since it takes a large amount of time to administer and interpret them. In order to help solve this problem, the use of decision trees is proposed. In this project, two questionnaires were created for the diagnosis of two different types of mental illness, and a decision tree algorithm was applied. As a result, both tests required, on average, only half the questions to reach a certain rating. Finally, an application was developed that allows us to easily administer the obtained tests